Computer graphics: principles and practice (2nd ed.)
Computer graphics: principles and practice (2nd ed.)
GPU-based 3D cone-beam CT image reconstruction for large data volume
Journal of Biomedical Imaging
Algorithm for hyperfast cone-beam spiral backprojection
Computer Methods and Programs in Biomedicine
Pushing the limits for medical image reconstruction on recent standard multicore processors
International Journal of High Performance Computing Applications
UWB microwave imaging for breast cancer detection: Many-core, GPU, or FPGA?
ACM Transactions on Embedded Computing Systems (TECS) - Special Issue on Design Challenges for Many-Core Processors, Special Section on ESTIMedia'13 and Regular Papers
Hi-index | 0.00 |
Expensive computational cost is a severe limitation in CT reconstruction for clinical applications that need real-time feedback. A primary example is bolus-chasing computed tomography (CT) angiography (BCA) that we have been developing for the past several years. To accelerate the reconstruction process using the filtered backprojection (FBP) method, specialized hardware or graphics cards can be used. However, specialized hardware is expensive and not flexible. The graphics processing unit (GPU) in a current graphic card can only reconstruct images in a reduced precision and is not easy to program. In this paper, an acceleration scheme is proposed based on a multi-core PC. In the proposed scheme, several techniques are integrated, including utilization of geometric symmetry, optimization of data structures, single-instruction multiple-data (SIMD) processing, multithreaded computation, and an Intel C++ compilier. Our scheme maintains the original precision and involves no data exchange between the GPU and CPU. The merits of our scheme are demonstrated in numerical experiments against the traditional implementation. Our scheme achieves a speedup of about 40, which can be further improved by several folds using the latest quad-core processors.